Mechanics & Industry
Volume 18, Number 7, 2017
STANKIN: Innovative manufacturing methods, measurements and materials
|Number of page(s)||7|
|Published online||30 December 2017|
Estimation of process capability indices from the results of limit gauge inspection of dimensional parameters in machining industry
Moscow State University of Technology “STANKIN”,
1 Vadkovsky per.,
127055, Russian Federation
* e-mail: firstname.lastname@example.org
Accepted: 21 November 2017
The process capability indices Cp, Cpk are widely used in the modern quality management as statistical measures of the ability of a process to produce output X within specification limits. The customer's requirement to ensure Cp ≥ 1.33 is often applied in contracts. Capability indices estimates may be calculated with the estimates of the mean µ and the variability 6σ, and for it, the quality characteristic in a sample of pieces should be measured. It requires, in turn, using advanced measuring devices and well-qualified staff. From the other hand, quality inspection by attributes, fulfilled with limit gauges (go/no-go) is much simpler and has a higher performance, but it does not give the numerical values of the quality characteristic. The described method allows estimating the mean and the variability of the process on the basis of the results of limit gauge inspection with certain lower limit LСL and upper limit UСL, which separates the pieces into three groups: where X < LСL, number of pieces is n1, where LСL ≤ X < UСL, n2 pieces, and where X ≥ UСL, n3 pieces. So-called Pittman-type estimates, developed by the author, are functions of n1, n2, n3 and allow calculation of the estimated µ and σ. Thus, Cp and Cpk also may be estimated without precise measurements. The estimates can be used in quality inspection of lots of pieces as well as in monitoring and control of the manufacturing process. It is very important for improving quality of articles in machining industry through their tolerance.
Key words: Statistical process control / grouped observations / process capability indices / narrow-limit gauging / Pittman-type estimates
© AFM, EDP Sciences 2017
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